Browsing by Author "Shin, Yung"

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    Optimization of Chessboard Scanning Strategy Using Genetic Algorithm in Multi-Laser Additive Manufacturing Process
    (ASME, 2021-02) Malekipour, Ehsan; Valladares, Homero; Shin, Yung; El-Mounayri, Hazim; Mechanical and Energy Engineering, School of Engineering and Technology
    Residual stress and manufacturing time are two serious challenges that hinder the widespread industry adoption and implementation of the powder-bed fusion (PBF) process. Commercial Multi-Laser PBF (ML-PBF) systems have been developed by several vendors in recent years, which dramatically increase the production rate by employing more heat sources (up to 4 laser beams). Although numerous research works conducted toward mitigation of the effects of residual stress on printed parts in the Single Laser PBF (SL-PBF) process, no research work on this topic has been reported for the ML-PBF process to date. One of the most efficient real-time approaches to mitigate the influence of residual stress and as such the process lead time effectively is to improve the scanning strategy. This approach can be also implemented effectively in the ML-PBF process. In this work, we extend the previously developed GAMP (Genetic Algorithm Maximum Path) strategy for optimizing the scanning path in ML-PBF. The E-GAMP (the Extended GAMP) strategy manipulates the printing topology of the islands and generates more thermally efficient scanning patterns for the chessboard scanning strategy in ML-PBF. This strategy extends the single thermal heat source to multiple ones (2 as well as 3 lasers). To validate the effectiveness of the proposed strategy, we simulate the thermal distribution throughout a simple rectangular layer by ABAQUS for both the traditional successive scanning strategy and the E-GAMP strategy. The results demonstrate that the E-GAMP strategy considerably decreases the manufacturing time while it reduces the maximum temperature gradient, or in other words, generates a more uniform temperature distribution throughout the exposure layer.
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    Thermo-fluid Topology Optimization and Experimental Study of Conformal Cooling Channels for 3D Printed Plastic Injection Molds
    (Elsevier, 2019) Jahan, Suchana; Wu, Tong; Shin, Yung; Tovar, Andres; El-Mounayri, Hazim; Mechanical and Energy Engineering, School of Engineering and Technology
    With the advent of additive manufacturing, innovative design methods, such as network-based techniques, and structural topology optimization have been used to generate complex and highly efficient cooling systems in recent years. However, methods that incorporate coupled thermal and fluid analysis remain scarce. In this paper, a coupled thermal-fluid topology optimization algorithm is introduced for the design of conformal cooling channels. The problem is formulated based on a coupling of Navier- Stokes equations and convection-diffusion equation. The problem is solved by gradient-based optimization after analytical sensitivity derived using adjoint method. With this method, the channel position problem is replaced to a material distribution problem. The material distribution directly depends on the effect of flow resistance, heat conduction, natural and forced convection. The algorithm leads to a two-dimensional conceptual design having optimal heat transfer and balanced flow, which is further transformed into three-dimensional cooling channel design. Here, a comprehensive study is presented, starting from design, simulation, 3D printing process and experimental testing of an injection mold with conformal cooling channels in industrial production environment. A traditional mold model is provided by an industrial collaborator. To enhance the overall thermo-fluid performance of the mold and improve final product quality, a redesign of this mold core is done with conformal cooling channels inside. The final design is 3D printed in pre-alloyed tool-steel powder Maraging Steel using Truprint 3000 metal 3D printing machine. The printed core required some heat treatment and finishing processes and added features to be incorporated to make it production ready. Once all the preparation was complete, the core was tested experimentally in a multicavity injection molding machine in real industrial environment at our industrial partner’s production facility. This paper describes all the steps starting from design, analysis, die 3D printing and finally ending at final experimental testing, as well as recommendations for tool designer and injection molding industry to implement additive manufacturing for their benefit. This paper is not just focused on a specific aspect such as design, simulation or manufacturing, but rather a comprehensive paper presenting a case study on implementation of topology optimization and additive manufacturing in real life industrial production scenario.